Hydrobiologia (2007) 583:57–68
DOI 10.1007/s10750-006-0470-z
PRIMARY RESEARCH PAPER
Density-dependent individual growth of marble trout
(Salmo marmoratus) in the Soca and Idrijca river basins,
Slovenia
Simone Vincenzi Æ Alain J. Crivellı̀ Æ Dusan Jesensek Æ
Jean-Francois Rubin Æ Giulio A. De Leo
Received: 29 August 2006 / Revised: 29 August 2006 / Accepted: 11 October 2006 / Published online: 3 March 2007
Springer Science+Business Media B.V. 2007
Abstract Although the main features of salmonid life cycles are currently well known, marble
trout (Salmo marmoratus) populations have been
scarcely studied due to the present limited geographical distribution of the species. In this work
we tested the hypothesis of density-dependent
individual growth of marble trout with data
gathered from multi-year on-going monitoring
started in 1996 in three streams (Zakojska,
Gorska and Gatsnik) in the Soca and Idrijca river
basins (Slovenia). As observed for other salmonid
species, marble trout exhibits high plasticity in
body size and growth in response to environmental conditions. Age-specific mean lengths are
Handling editor: J. Trexler
S. Vincenzi (&) G. A. De Leo
Dipartimento di Scienze Ambientali, Università degli
Studi di Parma, Parco Area delle Scienze 33/A,
43100 Parma, Italy
e-mail: [email protected]
A. J. Crivellı̀
Station Biologique de la Tour du Valat, Le Sambuc,
13200 Arles, France
D. Jesensek
Tolmin Angling Association, Modrej 26a,
65216 Most na Soci, Slovenia
J.-F. Rubin
Ecole d’ingénieurs HES, 150 route de Presinge,
1254 Jussy, Geneva, Switzerland
significantly different among the three streams.
Despite this variability, the statistical analyses
outlined some clear patterns. Mean lengths of
marble trout cohorts aged ‡1+ are correlated with
total population density in the first year of life of
the cohorts; the age-specific relationship between
mean length and total density is well explained by
negative power curves. Length of marble trout at
age 1+ is significantly correlated with length at
subsequent years up to age 4+. ANCOVAs
performed on the stream-specific datasets showed
a significant effect of total density of marble trout
on annual age-specific individual growth rates.
Von Bertalanffy’s body growth models were
calibrated on length–age data of Zakojska and
Gorska marble trout. Our analysis shows the
existence of density-dependent effects on growth
of marble trout that might be crucial in regulating
population dynamics.
Keywords Marble trout Salmo marmoratus Individual growth Density-dependent growth
Introduction
Identifying compensatory responses to changes in
population density is of crucial importance to our
understanding of the demography and dynamics
of structured populations. Competition for limiting resources or predation are commonly claimed
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58
as the main factors underlying density-dependent
patterns (i.e. Post et al., 1999). Density-dependent
mortality and density-dependent emigration are
phenomena widely described for stream-dwelling
salmonids, while density-dependent growth is
more difficult to detect in the wild (Grant &
Kramer, 1990). However, density-dependent
growth as a result of competition for food has
been described for many fish populations (e.g.
Beverton & Holt, 1957; Rochet, 1998; Jenkins
et al., 1999; Post et al., 1999; Imre et al., 2005),
even though, as noted by Lorenzen & Endberg
(2002), its importance as a mechanism of population regulation remains little appreciated. Given
the tight relationship between fecundity and body
size (Jenkins et al., 1999; Klemetsen et al., 2003),
density-dependence in individual growth in fish
populations is a potentially powerful mechanism
of population regulation. In fact, substantial
reduction in fish abundance in lakes are often
followed by high recruitment that either quickly
restores population sizes to pre-manipulation
levels or produces population cycles (Jenkins
et al., 1999). Recent studies by Jenkins et al.
(1999) on brown trout and by Imre et al. (2005)
on Atlantic salmon have demonstrated the occurrence of density-dependent individual growth in
salmonids in freshwater streams. A recent metaanalysis on density-dependent growth of juvenile
stream-dwelling salmonids by Grant & Imre
(2005) found that population density affects
individual growth via exploitative competition,
that is the depletion of food by competitors
(Keddy, 1989), at intermediate population densities (£1 fish m–2), while at higher densities, when
space is limiting, density mainly affects survival
via competition for suitable territory. Densitydependent growth in salmonid populations was
also reported by Hartman & Scrivener (1990),
Crisp (1993) and Newman (1993), suggesting that
this might be a general bottom-up regulating
mechanism for stream-dwelling salmonid populations (Imre et al., 2005).
Here, we explore the issue of density-dependent growth in three translocated populations of
the endangered marble trout Salmo marmoratus
(Cuvier) in the Soca and Idrijca river basin.
Among trout species, the marble trout Salmo
marmoratus (Dorofoyeva et al., 1992; Kottelat,
123
Hydrobiologia (2007) 583:57–68
1997) is of particular conservation interest, as
only a few pure populations exist today in a
restricted geographical distribution in the basin of
the Po River in northern Italy (Sommani, 1961;
Forneris et al., 1990; Giuffra et al., 1996), in the
Adriatic basin of former Yugoslavia (Povz, 1995)
and in Albania (Schoffmann, 1994). A conservation programme has been launched in Slovenia to
duplicate the existing pure populations (Fig. 1)
through translocation of pure marble trout in
fishless streams (Crivelli et al., 2000). Since 1996,
an annual monitoring programme has been carried out in order to assess the long-term persistence and the population dynamics of those new
populations.
The aim of the present study is to test the
hypothesis of density-dependence in individual
growth in the progeny of translocated marble
trout in pristine Slovenian mountain streams.
Although there are a number of studies dealing
with the description of somatic growth of salmonid populations, most of them focus on more
widespread species, such as brown trout Salmo
trutta L. (e.g., Jenkins et al., 1999; Vollestad et al.,
2002), rainbow trout Oncorhynchus mykiss (Walbaum) (e.g., Su et al., 1996; Gardeur et al., 2001),
and Atlantic salmon Salmo salar L. (e.g., Gardeur
et al., 2001; Imre et al., 2005). On the contrary,
Fig. 1 Map showing the location of S. marmoratus pure
populations and of the experimental streams within the
Soca and Idrijca river basins in Slovenia
Hydrobiologia (2007) 583:57–68
little is known on the individual growth dynamics
of marble trout, which is unfortunate, as the
quantitative analysis of somatic traits and investigation of density-dependence in individual
growth is a crucial step to understand the population dynamics, to assess the long-term viability
of the populations and the efficacy of rehabilitation projects for this species of great conservation
interest. Specifically, we tested the following
hypotheses: (1) population density significantly
affects the age-specific annual growth rates; (2)
mean body length at age x(1+ £ x £ 4+) of the
individuals of a cohort is negatively correlated
with total density of marble trout when the
individuals of the same cohort were aged 1+.
Materials and methods
Study area and species description
The Soca and Idrijca river basins present a
pristine environment with reduced agricultural
and industrial activities, absence of erosion due to
numerous deciduous forests—mainly Fagus sylvatica—, low population density and numerous
areas officially protected, such as the Triglav
National Park. Fly-fishing is one of the main
attractions for tourists and one of the most
profitable economic activities in the region,
attracting many anglers from abroad. Fly-fishing
is allowed only in the hybridisation zone in the
lowland part of the rivers. Eight genetically pure
populations (from 0% to 2% of foreign genes,
Berrebi et al., 2000; Crivelli et al., 2000; Fumagalli
et al., 2002), covering a length of 15 km (Fig. 1),
were discovered in the headwaters of the Soca
and Idrijca river basins, isolated from the hybridisation zone downstream by impassable
waterfalls. Trout is the only fish species present
within these streams and no predation by fisheating birds and macroinvertebrates has been
observed.
The remoteness of Zakojska, Gorksa and
Gatsnik limits human disturbance linked to recreational activities (e.g., angling). Gorska and
Zakojska are one-way streams, that is, marble
trout can move only from upstream pools to
downstream pools, while Gatsnik is a two-way
59
stream; Gorska is more fragmented than Zakojska while Gatsnik does not present any discontinuity. The main features of the three streams are
presented in Table 1 and in Fig. 2. Spawning
takes place in November–December while marble trout eggs generally hatch in April. Marble
trout reach sexual maturity at age 2+ and 3+ for
males and females, respectively, and show a clear
linear relationship between length of females and
number of eggs produced (Crivelli, pers. comm.).
Stocking material
In June 1996, 500 marble trout reared in the fish
farm were released as 1+ trout in fishless headwaters of Zakojska and Gorska streams. This
stocking material was the progeny of marble trout
females and marble trout males from the Zadlascica pure population (Fig. 1) caught in the wild in
autumn 1994; females were stripped in the river
and eggs reared up to fish aged 1+ within the fish
farm (Tolminka, Tolmin, Slovenia).
In June 1998, 599 trout reared in the fish farm
were released as 1+ trout in fishless headwaters of
Gatsnik stream. The Gatsnik stocking material
was the progeny of 26 marble trout females from
the Trebuscica (Fig. 1) pure population and 12
marble trout males from the Lipocscek (Fig. 1)
pure population caught in the wild in autumn
1996; females were stripped in the fish farm and
eggs reared up to fish aged 1+ within the fish farm.
Sampling procedure
After the introduction, stocked trout successfully
reproduced within the streams. Marble trout
hatched in the streams, along with stocking
materials, were sampled every June from 1997
to 2004 for Zakojska and Gorska and from 1999
to 2004 for Gatsnik on the whole length of each
stream starting from downstream to the upstream
extent. Using a gasoline-powered, portable backpack electrofishing unit, we electrofished every
stream two times to produce a multiple-pass
removal estimate of trout abundance using Microfish 3.0 (Van Deventer & Platts, 1989). All
captured fish aged ‡1+ and with a minimum size
of 115 mm (LT) were anaesthetized with benzocaine, marked with Carlin tags (Institute of
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Hydrobiologia (2007) 583:57–68
Table 1 Main features of
sanctuary streams and
parental cohorts
A sector is part of the
stream with an impassable
barrier (waterfall)
preventing the fish to
move upstream. IBGN
(AFNOR, 1992): Indice
Biologique Général
Normalisé (water quality
class: 1 = pristine to
5 = very polluted)
Main features
Gatsnik
Zakojska
Gorska
Length (m)
Surface area (m2)
Pool surface (m2)
(% of total surface)
Altitude range (m a.s.l.)
Number of sectors
Benthos biomass (mg m–2)
I.B.G.N (water quality class)
Stream type
Stocking date
Total number of fish
Mean total length (mm) ± s.d.
Mean weight (g) ± s.d.
Mean body condition (K) ± s.d.
2,021
6,035
2,375 (39.4%)
1,238
3,544
895 (25.3%)
845
1,805
685 (38%)
899–924
0
15,938
17(1)
Two-ways
June 1998
600
128.15 ± 15.77
22 ± 10
0.99 ± 0.09
578–728
7
14,638
16(2)
One-way
June 1996
500
115.15 ± 14.67
16 ± 8
1.01 ± 0.12
400–514
11
11,446
15(2)
One-way
June 1996
500
125.81 ± 15.54
22 ± 10
1.06 ± 0.12
altitude (m)
altitude (m)
Freshwater Research, Sweden), measured for
total length (LT, to the nearest mm) and weight
(W, g) and if sampled for the first time the
adipose fin was removed. Marble trout then were
returned live near the point of capture. Age was
determined by tag examination. Age designation
follows standard terminology; marble trout in the
first year of life were denoted as 0+ and in the
second year, subsequent to winter annulus formation, as 1+. At first marking, scales were taken
to assess the age of the fish. The small size of
marble trout aged 0+ prevents their sampling in
500
450
Gorska
400
700
650
Zakojska
altitude (m)
600
950
Gatsnik
900
0
500
1000
1500
2000
2500
length (m)
Fig. 2 Topographic profiles of the study streams. Vertical
bars indicate waterfalls preventing fish to move upstream.
Zakojska and Gorska are one-way streams, while Gatsnik
is a two-way stream. Gorska presents the highest number
of sectors
123
June and they are not taken into account in this
study. No sexing of trout caught could take place
in June. A total of 1,305, 432 and 3,862 marble
trout hatched within the streams were sampled in
Zakojska, Gorska and Gatsnik, respectively.
Data analysis
We carried out statistical analyses only on marble
trout hatched in the streams after introduction.
Stocking materials were not considered, as marble trout reared in the fish farm up to 1+ for the
rehabilitation project may exhibit growth patterns
quite different from those of marble trout naturally hatched within the streams and growing in
the wild.
Length and weight data were log transformed
to normalize the distributions. Assumption of
normality of distribution and homogeneity of
variances were tested through Shapiro–Wilk
(Shapiro & Wilk, 1965) and Levene’s (Levene,
1960) tests, respectively. We use analyses of
variance (ANOVA) to examine inter-population
and intra-population variability in somatic traits
across ages, and Tukey post-hoc tests (Tukey
honest significant difference) for pair-wise comparison of means within group analyses yielding
significant results.
Age-specific annual individual growth rates in
length GL (year–1) was computed as follows:
GL ðxÞ ¼ log
LT ðx þ 1Þ
LT ðxÞ
Hydrobiologia (2007) 583:57–68
where LT(x + 1) and LT(x) are the total length
of marble trout at age x + 1 and age x, respectively.
Correlation between LT at age 1+ and LT at
subsequent years was estimated by using Pearson’s r.
Total density of marble trout at the stream
level was estimated by dividing the total number
of marble trout (stocking material + marble trout
hatched within the stream) sampled for the
overall surface area of pools in each stream.
Differences in mean density across years among
streams were estimated by fitting a linear mixedeffect model (Pinheiro & Bates, 2000) with year
of sampling modelled as random effect within
streams. Differences in annual growth rate GL(x)
were tested with analysis of covariance
(ANCOVA) using, as explanatory variables,
age, length, total density of trout when the marble
trout is aged x and total density of trout when the
marble trout was in its first year of life.
Statistics were computed on each stream separately. When testing the relationship between
mean length at age x of the individuals of a cohort
and total density of marble trout when the
individuals of the same cohort were aged 1+, the
analysis was carried out also by pooling together
the stream-specific data sets to cover a wider range
of trout densities. The relationship between mean
length at age x of each cohort and total population
density during the first year of life of the same
cohort was tested by linear regression and by a
negative power curve, estimated from linear
regression after a logarithmic transformation of
length and density data. Akaike Information
Criterion (AIC, Motulsky & Christopoulos,
2004) was computed for each model; the model
with the smallest AIC value was considered to
offer a better fit if AICpower – AIClinear ‡ 2
(Motulsky & Christopoulos, 2004).
Mean stream-specific growth patterns were
investigated by fitting Von Bertalanffy’s growth
curves (Von Bertalanffy, 1938) in the form:
LðxÞ ¼ L1 ½1 expðkðx x0 Þ
where x is the age (years), L¥ is the maximum
length (mm), k is the Brody’s growth coefficient
61
relating age to length, and x0 is the age at which
length equals 0.
Von Bertalanffy’s growth parameters were
estimated using non-linear least-squares estimation. Von Bertalanffy’s growth curve could not be
estimated for Gatsnik, as marble trout have not
reached the maximum age in Gatsnik, thus
preventing the estimation of the asymptotic
length L¥. Differences in Von Bertalanffy’s
growth curve parameters L¥ and k between
Gorska and Zakojska were tested by a t-test
(Motulsky & Christopoulos, 2004) as follows:
bzakojska bgorska
t ¼ qffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi
Std.Err2zakojska Std.Err2gorska
where b is the parameter estimate and the
degrees of freedom for the t statistics are equal
to the sum of the df from each model fitting.
The significance level a for all statistical tests is
set at 0.05. All statistical analyses were performed
by using the statistical software R (R development Core Team, 2005).
Results
Age and growth of marble trout
Table 2 reports the basic statistics relative to
length, weight and age-specific growth rates in
length GL(x) of marble trout hatched in Zakojska, Gorska and Gatsnik. The first cohorts of
marble trout aged 1+ born in the streams were
sampled in year 1999, 2000 and 2001 for Gorska,
Zakojska and Gatsnik, respectively.
The mean age-specific lengths and weights
varied significantly among the streams for all
ages (ANOVA, p < 0.001 for all ages). In Gorska,
age-specific mean length was higher than in
Zakojska and in Gatsnik (Tukey test, p < 0.05
for all ages).
Length of marble trout at age 2+, 3+ and 4+
was positively correlated with length of the same
individual at age 1+ in each stream, except for
Gorska where length at age 4+ was not significantly correlated with length at age 1+, probably
due to the low number of samples (Table 3). The
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123
0.20 ± 0.06
0.09 ± 0.03
–
–
–
–
6.96
21.01
37.97
48.19
15.72 13.07 ±
22.42 45.08 ±
26.92 102.52 ±
25.22 195.58 ±
–
–
correlations were significant also when pooling
together the stream-specific datasets (Table 3).
Significant differences in mean GL(x) among
streams were found only from age 2+ to age 3+,
but subsequent comparison of means revealed
significant difference only between Gorska and
Gatsnik (Tukey test, p < 0.05). Growth of marble
trout is greatly reduced after the first years of life
(Table 2). Growth from age 2+ to 3+ was only 54,
44 and 46% of growth from age 1+ to 2+ in
Zakojska, Gorska and Gatsnik, respectively.
±
±
±
±
107.56
163.28
214.63
270.93
–
–
1,939
1,162
299
30
–
–
±
±
±
±
0.19
0.10
0.07
0.03
–
–
12.60
51.54
70.97
96.56
91.70
0.00
±
±
±
±
±
±
22.87
75.89
136.16
209.27
341.04
460.80
±
±
±
±
±
±
128.01
192.99
238.87
275.79
323.28
360.00
204
110
77
33
7
1
0.09
0.07
0.06
0.04
±
±
±
±
0.16
0.09
0.07
0.03
–
–
15.36 16.39 ± 6.54
27.83 57.91 ± 32.13
29.54 95.07 ± 46.25
31.03 142.17 ± 57.32
35.39 215.91 ± 90.80
24.04 366.35 ± 3.75
±
±
±
±
±
±
115.11
176.93
211.25
242.25
280.29
329.00
542
422
241
81
17
2
1+
2+
3+
4+
5+
6+
LT ± s.d
(mm)
N
Age
Stream Zakojska
W ± s.d (g)
GL ± s.d
(year–1)
LT ± s.d.
(mm)
20.66
36.75
39.54
41.82
22.28
0.00
W ± s.d (g)
0.09
0.07
0.05
0.05
LT ± s.d
(mm)
N
N
GL ± s.d
(year–1)
Gatsnik
Gorska
W ± s.d (g)
GL ± s.d
(year–1)
Hydrobiologia (2007) 583:57–68
Table 2 Basic statistics of marble trout sampled in Zakojska, Gorska and Gatsnik relative to total length (LT), weight (W) and age-specific annual individual growth
rate (GL)
62
Density-dependent effects
Data relative to marble trout population density
is reported in Table 4. Density of marble trout
varied annually within each stream. Density of
marble trout in ind. m–2 is significantly different
among streams, with Gorska presenting the lowest mean density. The ANCOVAs performed on
stream-specific datasets (Table 5) revealed that
GL(x) is affected by total density of marble trout
in the first year of life for Gorska and Gatsnik
trout populations and by total population density
when marble trout is aged x for the Gorska and
Zakojska marble trout populations. Analyses
performed using body weight instead of length
showed similar results.
There was no significant effect of total population density during the first year of life of the
cohort on mean length at age x of marble trout of
the same cohort when we tested each of the three
streams separately, neither when modelling the
pattern with negative power curve nor with linear
regression. However, when pooling together the
data of the three streams, mean length of each
cohort from age 1+ to age 4+ is negatively
correlated with total density of marble trout
(ind. m–2) when the individuals of the same
cohort where aged 1+ (Fig. 3). In each case, the
negative power curve provided a significantly
better fit of the density-dependent pattern than
the linear model. It was not possible to compute
the correlation between average length of 5+
cohorts and density during the first year of life of
the same cohorts due to the low number of
individuals in the sample. When density is measured in biomass (g m–2), fitting negative power
curves explain a smaller, yet significant, portion of
Hydrobiologia (2007) 583:57–68
63
Table 3 Correlation (Pearson’s r) between length of marble trout at age 1+ and length at age 2+, 3+ and 4+ for Zakojska,
Gorska and Gatsnik separately and using the combined dataset
Ages
Zakojska
Gorska
Gatsnik
Combined
1+ fi 2+
1+ fi 3+
1+ fi 4+
0.70 (145)**
0.42 (74)**
0.55 (15)*
0.67 (67)**
0.41 (37)*
0.37 (14)n.s
0.71 (156)**
0.42 (64)**
0.63 (18)*
0.69 (368)**
0.45 (175)**
0.39 (47)**
Sample size is reported in parenthesis. ** p < 0.01; * p < 0.05;
n.s
Table 4 Population density of marble trout in terms of
number (N, fish m–2) and biomass (B, g m–2)
reported in Table 6. The t-tests showed significant
differences in L¥ but not in k between Zakojska
and Gorska.
Stream
Density 1999 2000 2001 2002 2003 2004
Zakojska N
B
Gorska
N
B
Gatsnik N
B
–
0.20 0.36 0.41 0.34 0.28
–
18.91 28.58 34.65 29.80 27.28
0.08 0.05 0.14 0.16 0.13 0.18
14.96 6.61 10.68 13.84 14.95 17.39
–
–
0.10 0.37 0.57 0.47
–
–
9.21 10.78 21.31 22.70
p > 0.05
Discussion and conclusions
It is well known that salmonid species usually
present remarkable variations in somatic and
demographic traits resulting from either genetic
differences or from plasticity in growth rates in
response to variable environmental conditions
(Klemetsen et al., 2003). Our analysis shows that
variations in somatic traits, like mean age-specific
length and weight, also were notable across the
three translocated marble trout populations in
Slovenian mountain streams. Despite this variability, some common patterns can be detected in
all the three populations.
The annual variation in total density of marble
trout within and across streams might be partially
the variability of mean length of marble trout
cohorts for all ages.
Von Bertalanffy’s growth model
The Von Bertalanffy’s growth curve was estimated on 1,305 and 432 length–age data for
Zakojska and Gorska, respectively (Fig. 4).
Von Bertalanffy’s growth curve parameters are
Table 5 ANCOVAs of the effects of age (categorical variable), length, trout density at age x (Density x) and trout density
during the first year of life (Density as UnderYearling) on annual growth rate GL(x) in the three experimental streams
Source of variation
Zakojska (R2 = 0.91)
Age
Length
Density x
Density as UY
Residuals
Gatsnik (R2 = 0.94)
Age
Length
Density x
Density as UY
Residuals
Gorska (R2 = 0.89)
Age
Length
Density x
Density as UY
Residuals
SS
F
df
Regression coefficients
Std. Err.
p-value
6.19
0.27
0.04
0.0001
2.3369
280.24
50.05
6.65
0.0201
–
4
1
1
1
423
–
–0.001
–0.18
0.007
–
0.0001
0.07
0.05
–
<0.01
<0.01
<0.01
>0.05
–
3.42
0.24
0.06
0.02
2.555
238.91
49.73
1.35
5.50
–
3
1
1
1
535
–
–0.001
0.24
–0.44
–
0.0001
0.20
0.19
–
<0.01
<0.01
>0.05
<0.01
–
2.97
0.22
0.13
0.05
1.3265
83.42
25.03
14.67
5.64
–
4
1
1
1
–
–0.001
–1.24
–0.57
–
0.0002
0.32
0.24
<0.01
<0.01
<0.01
<0.05
–
123
250
150
100
150
100
R2=0.66, p<0.001
R2=0.73, p<0.001
0.0 0.1 0.2 0.3 0.4 0.5 0.6
300
Age 4+
150
R2=0.58, p<0.01
0.0 0.1 0.2 0.3 0.4 0.5 0.6
100
150
200
250
300
Age 3+
250
Average total length (mm)
200
Zakojska
Gorska
Gatsnik
0.0 0.1 0.2 0.3 0.4 0.5 0.6
100
Age 2+
200
250
300
Age 1+
200
Fig. 3 Average length of
marble trout cohorts
relative to marble trout
density (ind. m–2) during
the first year of life of the
cohort pooling together
the stream-specific data
sets. Negative power
curves and nonparametric boostrap 95%
confidence limits are
shown for each age
Hydrobiologia (2007) 583:57–68
300
64
R2=0.62, p<0.05
0.0 0.1 0.2 0.3 0.4 0.5 0.6
−2
Density of marble trout (ind m
explained by the topographic and physical features of the streams (Fig. 2). It is well known that
the availability of shelters and suitable microhabitat for juveniles are limiting factors for population abundance (Lobón-Cerviá & Rincón, 2004).
Further studies will be necessary to determine
whether stream discharge combined with stream
morphology is a crucial determinant of
Fig. 4 Von Bertalanffy’s
growth curve (solid line)
and 95% confidence
intervals (dashed lines) as
estimated from marble
trout sampled in Zakojska
and in Gorska. Parameter
estimates are reported in
Table 6
123
)
population size, as argued by Lobón-Cerviá &
Rincón (2004), also for the three streams under
study. Despite this caveat, the results of our
analysis suggest that density-dependence in individual growth of marble trout may indeed occur
in the studied system (Table 5). The relationship
between average length of marble trout cohorts
from age 1+ to 4+ and total population density
Hydrobiologia (2007) 583:57–68
Table 6 Basic statistics of
Von Bertalanffy’s growth
curve parameters for
Zakojska and Gorska
65
Stream
Parameters
Estimation
Std. Err.
2.5–97.5th
Zakojska
L¥ (mm)
t0 (mm)
k (year–1)
L¥ (mm)
t0 (mm)
k (year–1)
318.24
–0.34
0.34
376.76
–0.33
0.31
13.14
0.07
0.03
17.59
0.04
0.03
294.69–351.27
–0.49 to –0.20
0.27–0.41
345.75–418.66
–0.40 to –0.26
0.25–0.36
Gorska
during the first year of life of the cohorts was nonsignificant at the stream level, probably because
of the small range of variation of population
density within each stream. On the other hand, as
argued by Jenkins et al. (1999), the detection of
density-dependence patterns is obviously easier
when data span over a wide range of densities. In
fact, when pooling the datasets of the three
streams together, our study provides statistical
evidence of the effect of total density during the
first year of life on mean length of marble trout
cohorts from age 1+ to age 4+. Our results are in
agreement with those of Jenkins et al. (1999) for
S. trutta and Imre et al. (2005) for S. salar, who
hypothesized that body size of underyearlings
follows a negative power curve in relation to fish
density. Other studies suggest a curvilinear relationship between average body size or growth
rate and population density (e.g. Hartman &
Scrivener, 1990; Crisp, 1993; Newman, 1993), thus
implying that this might be a general pattern for
stream-dwelling salmonids.
The evidence gathered by Jenkins et al. (1999)
and by Imre et al. (2005) in favour of densitydependent growth of underyearling of salmonid
and the results of our study seem to suggest that
the total population density during the first year
of life may affect the growth pattern of marble
trout during the entire life span. In fact, we also
found a positive correlation between length at age
1+ and length at subsequent years (Table 3); this
means that larger marble trout at age 1+ tend to
remain larger also at older ages. This might have
important implications for the population dynamics of the marble trout: if larger trout are expected
to spawn more and/or produce larger eggs (Koops
et al., 2004), density-dependency in individual
growth rate from hatching up to age 1+ may affect
the overall reproductive output of the trout
during its entire reproductive life span, as already
argued by Lobón-Cerviá et al. (1997) for S. trutta
in the Esva River (Spain). A number of studies
reported a general correlation between rapid
growth and early sexual maturation (Hutchings
& Jones, 1998; Utrilla & Lobón-Cerviá, 1999);
accordingly, trout growing relatively slowly could
delay sexual maturation in order to reach the
minimum size required for gonad development.
This phenomenon was already observed for
brown trout in the Esva River (Spain) (e.g.
Lobón-Cerviá et al., 1997), though the nature of
phenotypic covariation between body size and
age of sexual maturity in salmonids is still not
completely understood (Martyniuk et al., 2003).
In lakes, reductions in density are commonly
followed by high recruitment, a mechanism possibly leading to fluctuation in fish abundance
(Hamrin & Persson, 1986; Townsend & Perrow,
1989; Persson et al., 1993; Tonn et al., 1994). In
streams, these density-related fluctuations could
be more difficult to detect; in fact, it is well known
that exogenous environmental factors (such as
floods or droughts) can cause the population to
collapse to very low densities before endogenous
intrinsic density-dependent regulation mechanisms take place (Lobón-Cerviá & Rincón,
2004). However, given the observational nature
of our data and the sampling interval of one
year, we cannot exclude that other factors
affecting growth, such as food abundance (Imre
et al., 2004) or water temperature (Egglishaw &
Shackley, 1985), might explain the observed
pattern of body growth. As for the potential
mechanism of density-dependent growth, the
analysis carried out in our three experimental
streams suggests that density-dependent growth is
probably caused by exploitation rather than
interference competition, as evidenced also by
Grant & Imre (2005) for juvenile stream-dwelling
salmonids at densities £1 fish m–2. Post et al.
123
66
(1999) observed that in organisms with plastic
growth, exploitative competition typically results
in reduction in the growth rate of all individuals
when food abundance is limiting. As noted by
Imre et al. (2005), in the case of exploitative
competition for a renewing resource, such as
stream drift, the per capita foraging rate will
decrease as 1/n – n being the number of competitors (Kramer et al., 1997)—thus following a
negative power curve.
From a population regulation point of view,
high individual growth at low densities may
enable the marble trout populations to rebound
quickly after catastrophic events, such as landslides, droughts and floods. On the other hand, as
noted by Jenkins et al. (1999), density-dependent
growth may impose an upper limit to population
abundance, through at least two mechanisms.
First, density-dependent growth, especially during
the first year of life, could translate into densitydependent survival over the first winter as argued
by Post et al. (1999); second, as fecundity in
marble trout is positively related to female length,
density-dependence in growth should limit the
egg production of a population.
The presence of density-dependence in individual growth in marble trout is an important
issue for conservation managers, particularly for
translocations of marble trout in fishless streams
to enhance the viability of the species. As stressed
by Grant & Imre (2005), a successful recovery
programme needs to maximize recruitment without wasting the stocking resource. In this sense,
our results suggest that particular attention must
be paid to the number of fish introduced when
stocking marble trout; in fact, given the tight
relationship between body length and number of
eggs produced, the density-dependence in individual growth and the other compensatory
responses observed in freshwater salmonids
(Rose et al., 2001) are likely to regulate the
population abundance and allow it to reach its
upper limit in a few generations. In addition, to
avoid the negative effects of density-dependent
growth, scatter stocking is preferable to point
stocking. As noted by Berg & Jørgensen (1991)
stocking fish at higher densities than the carrying
capacity of the stream could be more harmful
than beneficial, as the consequent overall reduced
123
Hydrobiologia (2007) 583:57–68
growth rate may result in a collapse of the trout
population in the stream.
For marble trout, the individual annual growth
rate in length GL(x) decreases as age increases,
therefore it is appropriate to fit a Von Bertalanffy
growth curve to model the growth of marble
trout. Von Bertalanffy’s growth curves were
calibrated on age-length data only for marble
trout from Zakojska and Gorska (Table 6).
Beverton & Holt (1957) argued that densitydependent growth mediated by food competition
is expected to affect the asymptotic length L¥.
Our findings indeed suggest a crucial role of
population density in determining asymptotic
length L¥ (Table 6). Comparison of Von Bertalanffy growth parameters among different species
of salmonids living in different environments
should be interpreted cautiously, not only because of species-specific differences but also
because individual growth is strongly influenced
by environmental factors such as temperature
(Elliot, 1975a, b; Edwards et al., 1979), invertebrate food (McFadden & Cooper, 1962) and
water current (Mason, 1976). Von Bertalanffy
growth parameters have been estimated for S.
trutta individuals sampled in Old Castile (Spain)
(L¥ = 659 mm; k = 0.18 year–1) (Lobón-Cerviá
et al., 1986), Schleswig-Holstein (Germany)
(L¥ = 570; k = 0.28) (Froese & Pauly, 2005) and
Afon Cwm (Wales) (L¥ = 216; k = 0.31) (Crisp &
Beaumont, 1995). The amount of variation
observed in growth patterns of salmonids seem
to be a phenotypic adaptation to local ecological
conditions, as shown by the experiment by Mann
et al. (1983).
The results presented here are not conclusive
yet, however, we are confident that our analysis of
individual marble trout growth in Slovenian
streams evidences the existence of density-dependent effects on growth that might be crucial to
regulate its population dynamics.
Acknowledgements We thank Fondation Tour du Valat
and the Angling Association of Tolmin for funding this
study. All the people who have participated each year to
the fieldwork are warmly thanked. We thank Patrick
Clevestam and Magnus Gehlin for helping us to get the
Carlin marks, and S. Sumer for undertaking IBGN and
benthos biomass investigations. We also thank Marino
Gatto for helpful review of the manuscript. The author
Hydrobiologia (2007) 583:57–68
also thanks three anonymous referees for their valuable
suggestions to improve a first draft of the MS. The authors
thank the Italian Minister of Research for having partially
supported the present work under an internationalization
project.
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